Business Intelligence with Python and Pandas: Data-Driven Insights Training Course

Introduction

Python has become the backbone of modern data analysis, and when combined with the Pandas library, it becomes a powerful tool for extracting, transforming, and analyzing data for Business Intelligence (BI). Organizations today rely on Python and Pandas to process massive datasets, build insightful reports, and make faster, more informed business decisions. This training course equips professionals with the knowledge and skills needed to harness Python and Pandas for BI applications.

Participants will learn how to perform data cleaning, transformation, aggregation, and visualization, all while applying real-world BI use cases. By the end of the program, learners will be able to transform raw business data into meaningful insights, design advanced analytics solutions, and support evidence-based decision-making through Python and Pandas.

Duration: 10 Days

Target Audience

  • Business intelligence professionals
  • Data analysts and data scientists
  • Python developers exploring BI applications
  • IT and BI project managers
  • Business managers seeking to leverage BI tools

10 Objectives

  1. Understand the role of Python and Pandas in BI applications
  2. Learn data import, cleaning, and preparation techniques
  3. Perform advanced data transformations and aggregation
  4. Apply statistical methods for BI insights using Python
  5. Create visualizations with Pandas and complementary libraries
  6. Automate BI workflows with Python scripting
  7. Integrate Python and Pandas with databases and BI platforms
  8. Develop predictive and prescriptive analytics solutions
  9. Apply Pandas to real-world BI case studies
  10. Deliver actionable BI insights through Python-based reporting

15 Course Modules

Module 1: Introduction to Python for BI

  • Overview of Python in BI
  • Installing Python and key libraries
  • Jupyter notebooks for analysis
  • Python basics for BI professionals
  • Real-world BI use cases

Module 2: Introduction to Pandas

  • Understanding data structures: Series and DataFrames
  • Creating and manipulating DataFrames
  • Indexing and selection methods
  • Handling metadata and data types
  • Loading data with Pandas

Module 3: Data Import and Export

  • Reading CSV, Excel, and SQL databases
  • Importing JSON and XML files
  • Web scraping with Pandas
  • Exporting to multiple formats
  • Handling large datasets

Module 4: Data Cleaning Essentials

  • Handling missing data
  • Removing duplicates
  • Data type conversions
  • Standardizing data formats
  • Outlier detection and handling

Module 5: Data Transformation with Pandas

  • Filtering and sorting data
  • Applying functions across datasets
  • Merging and joining DataFrames
  • Grouping and aggregation
  • Pivot tables and reshaping data

Module 6: Exploratory Data Analysis (EDA)

  • Descriptive statistics with Pandas
  • Summarizing categorical data
  • Correlation analysis
  • Identifying patterns in data
  • Initial insights for BI

Module 7: Data Visualization with Pandas

  • Built-in Pandas plotting functions
  • Line, bar, and scatter plots
  • Histograms and boxplots
  • Advanced visualization with Pandas styling
  • Practical visualization exercises

Module 8: Advanced Visualization with Python Libraries

  • Integrating Pandas with Matplotlib
  • Seaborn for statistical visualization
  • Plotly for interactive dashboards
  • Best practices in BI visualization
  • Case studies in visualization

Module 9: Statistical Analysis with Pandas

  • Probability and distributions
  • Hypothesis testing
  • Regression analysis
  • Time series decomposition
  • Statistical insights for BI

Module 10: Time Series Analysis with Pandas

  • Date and time handling
  • Resampling and frequency conversion
  • Rolling windows and moving averages
  • Trend and seasonality detection
  • Forecasting basics

Module 11: Automating BI Workflows with Python

  • Writing reusable scripts
  • Automating data imports
  • Scheduling BI tasks
  • Error handling in workflows
  • Building automated BI pipelines

Module 12: Working with Databases in Pandas

  • SQL integration with Pandas
  • Querying databases with Python
  • Loading data directly from SQL
  • Writing data back to databases
  • Best practices for BI database connections

Module 13: Integrating Python with BI Tools

  • Python and Power BI integration
  • Using Python in Tableau
  • Python with cloud BI platforms
  • Enhancing dashboards with Python scripts
  • Extending BI functionality

Module 14: Case Studies in Business Intelligence with Pandas

  • Sales and revenue analysis
  • Customer segmentation and churn analysis
  • Financial forecasting
  • Marketing campaign analysis
  • Operational efficiency insights

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport Pick Up is provided by the institute. Accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

 

Business Intelligence With Python And Pandas: Data-driven Insights Training Course in Gambia
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